Yes, the method will just 'run'. Unless there is an exception raised in that method, there is nothing that would prevent the method from not get executed successfully. If you want to know the state of the task after all your work is done, just get the Task instance from...

I suggest looking into Task Parallel Library. Starting with the .NET Framework 4, the TPL is the preferred way to write multithreaded and parallel code. Since you also need the result back from GetTXPower, I would use a Task<double> for it. Task<double> task = Task.Factory.StartNew<double>(GetTXPower); Depending on when you need...

After discussion, the straight answer is: No. Simply because multi-processing is not some magical trick that automatically offloads the burden on one processor to another. The developer needs to know how a program should split up a task, and specify that each task should take up a new process. So...

Are there any frameworks available in Java like EXECUTOR Framework which can do this task? I suggest you to take a look at the Akka framework for writing powerful concurrent & distributed applications. Akka uses the Actor Model together with Software Transactional Memory to raise the abstraction level and provide...

Thrust interprets ordinary pointers as pointing to data on the host: thrust::reduce_by_key(d_list, d_list+n, d_ones, C, D,cmp); Therefore thrust will call the host path for the above algorithm, and it will seg fault when it attempts to dereference those pointers in host code. This is covered in the thrust getting started...

It's all in the variables. Take, for instance, your p object. You pass the same p object to both threads. Now, I'm not sure if Parallel.Invoke is capable of detecting this, and as such is executing them in serial (albeit with significant overhead) or not, but I do know that...

You are practically resetting n to zero by each thread. Only the thread with tid==0 will increment n prior to printing. Even here, you may encounter the program to print I'am 0, this is my n: 0 instead of the expected I'am 0, this is my n: 1 since you...

TikZ (prefered solution) If you're already familiar with TikZ the respective magic is probably the best option. To use it, simply clone this repo into your .ipython/extensions directory and load the extension as shown in the example notebook with %load_ext tikzmagic. I just tried with IPython 3.1 and it works...

~/.ipython/kernels.json is not the right path. And theses files are not ment to be edited by hand. Also the file you have is not valid json, the server will be unable to read it if it was in the right place. use python2.7 -m IPython kernelspec install-self and python3 -m...

Please help me figure out what I'm doing wrong regarding the dictionaries. The exception is thrown because List<T> is not thread-safe. You have a shared resource which needs to be modified, using Parallel.ForEach won't really help, as you're moving the bottleneck to the lock, causing the contention there, which...

Here you create an infinite stream and limit it afterwards. There are known problems about processing infinite streams in parallel. In particular there's no way to split the task to equal parts effectively. Internally some heuristics are used which are not well suitable for every task. In your case it's...

You are doing to mallocs that are never freed on each iteration of the loop. This is why you are running out of memory. Also, your loop is using an unsigned int variable, which could be a problem depending on the value of maxGloablThreads....

The huge difference in execution time is caused by Math.random() method. If you will dig into its implementation you will see that it uses static randomNumberGenerator that is shared across all threads. If you go one step deeper then you will notice that execution is relying on int next(int) method,...

You could define any necessary auxiliary functions inside the model function. In this case: toy_model_parallel <- function(x){ f <- function(x){ x = x^2 } set.seed(x[1]) 2 * x[2] + f(2) + rnorm(1,0,0.1) } It looks like you need to do any worker initialization at the beginning of this function. So...

Merge provides an overload which takes a max concurrency. Its signature looks like: IObservable<T> Merge<T>(this IObservable<IObservable<T>> source, int maxConcurrency); Here is what it would look like with your example (I refactored some of the other code as well, which you can take or leave): return Observable //Reactive while loop also...

The approach to return the function seems elegant but unfortunately, unlike JavaScript, Julia does not resolve all the variables when creating the functions. Technically, your training function could produce the source code of the function with literal values for all the trained parameters. Then pass it to each of the...

If you attempt to execute some SPARQL request on your local fuseki server through a python script, you could be disturbed by some proxy problem. To resolve the problem you could use the auto-detect property of urllib. from SPARQLWrapper import SPARQLWrapper, JSON, XML #import urllib.request module. Don't forget for Python...

Your Hen class is poorly adapted to the Stream API. Provided that you cannot change it and it has no other useful methods (like Collection<Egg> getAllEggs() or Iterator<Egg> eggIterator()), you can create an egg stream like this: public static Stream<Egg> eggs(Hen hen) { Iterator<Egg> it = new Iterator<Egg>() { @Override...

This happens because adding the same patch (or, more generally, the same Artist) to more than one Axes is not supported: the Artist can only hold the necessary transform for use in one Axes. Future versions of matplotlib will raise an exception when the user tries to add an Artist...

As usual, Paul Betts has answered a similar question that solves my problem: The question: Reactive Extensions Parallel processing based on specific number Has some information on using Observable.Defer and then merging into batches, using that I've modified my previous code like so: return inputs.Select(i => new AccountViewModel(i)) .ToObservable() .ObserveOn(RxApp.MainThreadScheduler)...

You have to redirect your output to the systems standard output device. This depends on your OS. On Mac that would be: import sys sys.stdout = open('/dev/stdout', 'w') Type the above code in an IPython cell and evaluate it. Afterwards all output will show up in terminal....

When you call an async method you should await the returned task, which you can only do in an async method, etc. Awaiting the task makes sure you continue execution only after the operation completed, otherwise the operation and the code after it would run concurrently. So your code should...

I write this as an answer, although this is more or less a comment. One "hacky" way is to overwrite input or make a generator which returns an input-function with a constant return value. So kind of mocking it… def input_generator(return_value): def input(): return return_value return input This will work...

Why the unroll part do not need to sync thread after each step is done? The sample is incorrect, a barrier is indeed required after each step. It looks like the sample is written in warp-synchronous style, which is a way of exploiting the underlying execution mechanism of the...

First, better to use Interlocked.Increment(ref failedFiles) instead of failedFiles++. Otherwise it can happen that you have 10-15 failures, but you end up with a counter with a value something like 7-8, because of the lack of cache synchronization and the effect of compiler/jitter optimizations. The loop of your program might...

So my whole ordeal was with trying to use my code on a directory with a lot of files. In order to get rid of the errer stating that there are too many Arguments, I used this code that I gathered from previous Ole Tange posts: ls ./ | grep...

makes the web request calls (unrelated, so could be fired in parallel) What you actually want is to call them concurrently, not in parallel. That is, "at the same time", not "using multiple threads". The existing code appears to consume too many threads Yeah, I think so too. :)...

The main problem is that you're not enclosing the body of the foreach loop in curly braces. Because %dopar% is a binary operator, you have to be careful about precedence, which is why I recommend always using curly braces. Also, you shouldn't use c as the combine function. Since svm...

After searching some more, I got the impression that this (same scrollId) is by design. After the timeout has expired (which is reset after each call Elasticsearch scan and scroll - add to new index). So you can only get one opened scroll per index. https://www.elastic.co/guide/en/elasticsearch/reference/current/search-request-scroll.html states: Scrolling is not...

It appears to me that both of the workers are doing as much work as is performed in the sequential version. The workers should only perform a fraction of the total work in order to execute faster than the sequential version of the code. That might be accomplished by dividing...

As you mention in your question, you need to use parVar and packages. The packages vector should list any packages that you use, e.g. you use a random number generator that is found in another package. The parVar vector should contain in functions or variables that are called by your...

This code will work for very specific dimensions but not for others. It will work for square matrix multiplication when width is exactly equal to the product of your block dimension (number of threads - 20 in the code you have shown) and your grid dimension (number of blocks -...

If you do vector_sum(a) the local variable result will be the integer "1" in your first step which is not iterable. So I guess you simply should call your function vector_sum like vector_sum([a,b,a]) to sum up multiple vectors. Latter gives [4,7,10] on my machine. If you want to sum up...

Since you have exactly two branches here, it'll be best to dispatch parallel jobs to separate threads using future function. future will return you a future object (a special promise which will be automatically resolved when the job will be completed). Here is how it will look: (defn some-entry-point [obja...

Parallel prefix sum is a classical distributed programming algorithm, which elegantly uses a reduction followed by a distribution (as illustrated in the article). The key observation is that you can compute parts of the partial sums before you know the leading terms.

It depends on how specifically you don't want to "track request objects". Generally, nothing will guarantee that the calls are done other than just waiting for the requests. However, the way you're doing it isn't the simplest way. Instead, use MPI_WAITALL. MPI_Iallreduce(..., requests[0]); ... MPI_Iallreduce(..., requests[n-1]); MPI_Waitall(n, requests, MPI_STATUSES_IGNORE); This...

In 1.0, the functionality was bound to ( and tab and shift-tab, in 2.0 tab was deprecated but still functional in some unambiguous cases completing or inspecting were competing in many cases. Recommendation was to always use shift-Tab. ( was also added as deprecated as confusing in Haskell-like syntax to...

This seems to work. I like it better than the other solutions proposed here because: It's lot less code than an implicit class and slightly less code than using getOrElse with foldLeft. It uses the merged function from the API which's intended to do what I want. It's my own...